Joobold

Joobold — CS2 Stats

76561198260273232[U:1:300007504]Steam profile ↗✓ No bans

68Tracked matches44%Win rate2026Tracked since
CSDB Rating3.3 LearningSupport
Ladder ranks via Leetify

Performance scores

Aim46
Positioning18
Utility25

0–100 skill scores via Leetify.

Recent form

STEADY27–33–8Last 6840%Win rateWWWWLLLWWL

Last 10 vs previous 10: +30pp win rate · +0.02 avg rating · +0.6pp headshot accuracy · +17ms reaction

Win rate up 30pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 4–1 · 80% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 22%
  • Avg reaction 733ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 16%
  • Avg reaction 677ms

Last 20

  • 9–9–2 · 45% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 16%
  • Avg reaction 668ms

Newest first, from the last 68 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Support — Utility contribution stands above the rest of this profile (+1.1 against its own average).

Aim4.6
Utility2.5
Positioning1.8
Opening Duels0.0

Limited utility dependence

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

ZywOo

Plays most like ZywOo 93% playstyle similarity

Most alike: opening-duel success, utility contribution.

Where you differ: lower aim profile; lower positioning profile.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

Strengths & areas to improve

Areas to improve

Reaction time. 647ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Generated by fixed rules over this profile's own numbers — no model, no guessing; silent when the sample is too small to support a claim.

CSDB Rating breakdown

Aim4.6
Positioning1.8
Utility2.5
Mechanics6.0
Opening Duels0.0
Win Impact3.1

Composite 3.3/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.05+0.00
first ⅓ avg -0.05 → last ⅓ avg -0.05
Reaction time663ms−2ms
first ⅓ avg 665ms → last ⅓ avg 663ms
Headshot accuracy15.4%+4.0%
first ⅓ avg 11.5% → last ⅓ avg 15.4%

Rolling 5-match average across the last 68 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.09Best match rating · 13–0 · dust2, 3 Sept →
50%Best headshot accuracy · 13–0 · dust2, 3 Sept →
469msFastest reaction time · 6–13 · ancient, 20 Aug →
13–0Biggest win · dust2, 3 Sept →

Across the last 68 tracked matches.

Highlights

4Longest win streak
W4Current streak

Map breakdown

dust2Best map · 50% over 6infernoWeakest map · 29% over 7
MapGradePlayedRecordWin rateAvg rating
officeC4017–2343%-0.05
ancientC104–640%-0.06
infernoD72–529%-0.05
dust2B63–350%-0.02
cache—31–233%-0.06
anubis—20–20%-0.07

Across the last 68 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

14.7%Headshot accuracy
33.1%Accuracy (enemy spotted)
31.7%Spray accuracy
76.8%Counter-strafing
11.2°Preaim
647msReaction time
15.2%T opening success
10.8%CT opening success
0.24Enemies flashed / flash
2.0%Flash assists
7.43HE damage / grenade
1.86Flashes / match

Recommended for you

Chosen by comparing your tracked metrics against the thresholds we flag — the measurement behind each one is shown, so you can disagree with it.

  1. Best CS2 Crosshair

    Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.

    Headshot accuracy 14.7364% — below the 15% mark we flag

    Aim Training →
  2. Grenades & Utility

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.2375 — below the 0.5 mark we flag

    Grenade Lineups →
  3. Advanced Mechanics

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 15.162% — below the 40% mark we flag

Spend your practice time on Inferno

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

29% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
office13–6-0.1224%3 Sept →
inferno13–80.0022%3 Sept →
dust213–00.0950%3 Sept →
ancient13–10-0.089%3 Sept →
office7–130.015%1 Sept →
cache8–13-0.068%1 Sept →
ancient4–13-0.120%1 Sept →
ancient13–8-0.0227%1 Sept →
ancient13–9-0.043%1 Sept →
ancient3–13-0.0714%1 Sept →
office13–5-0.090%30 Aug →
dust213–10-0.0313%30 Aug →
anubis6–13-0.095%30 Aug →
inferno13–7-0.0135%30 Aug →
inferno8–13-0.0515%30 Aug →
dust212–12-0.0619%20 Aug →
ancient6–13-0.1315%20 Aug →
office3–13-0.0726%20 Aug →
office4–13-0.0115%20 Aug →
anubis12–12-0.0513%19 Aug →
inferno1–13-0.0812%19 Aug →
cache4–13-0.089%19 Aug →
office13–7-0.059%19 Aug →
dust27–13-0.1010%18 Aug →
office5–13-0.1525%18 Aug →
office13–10-0.0425%18 Aug →
office12–12-0.045%18 Aug →
office6–13-0.067%18 Aug →
dust213–5-0.0117%17 Aug →
inferno7–13-0.1018%17 Aug →
office13–9-0.0411%17 Aug →
office12–120.0114%17 Aug →
ancient12–12-0.069%16 Aug →
office13–8-0.047%16 Aug →
office10–13-0.0812%16 Aug →
office5–13-0.0417%16 Aug →
office13–4-0.0210%12 Aug →
ancient7–13-0.0115%12 Aug →
ancient4–13-0.1022%12 Aug →
office8–13-0.0313%11 Aug →
office12–12-0.0916%11 Aug →
ancient13–20.0616%10 Aug →
inferno12–12-0.0313%10 Aug →
office12–120.018%10 Aug →
office6–130.0212%10 Aug →
office11–130.0414%9 Aug →
office13–9-0.0110%6 Aug →
office13–6-0.0211%6 Aug →
office13–100.0510%5 Aug →
office10–13-0.105%5 Aug →
office9–13-0.109%5 Aug →
office4–13-0.057%2 Aug →
office13–11-0.0414%2 Aug →
office13–5-0.0825%2 Aug →
office13–7-0.0211%28 Jul →
office13–0-0.050%28 Jul →
office6–13-0.069%25 Jul →
office8–2-0.0123%25 Jul →
office13–50.016%25 Jul →
office2–13-0.134%13 Jul →
office2–13-0.107%13 Jul →
dust29–13-0.0326%12 Jul →
inferno7–13-0.0613%12 Jul →
cache7–2-0.0525%12 Jul →
office13–5-0.023%9 Jul →
office4–13-0.147%9 Jul →
office7–13-0.0720%17 Jun →
office5–13-0.098%17 Jun →

Match data via Leetify.

Recent teammates

Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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